Visualizing Spatial Data#

arcgisapi

1. ArcGIS API for Python#

The ArcGIS API for Python, i.e., the arcgis package, is a powerful, modern and easy to use Pythonic library to perform GIS visualization and analysis, spatial data management and GIS system administration tasks that can run both in an interactive fashion, and using scripts.

The package is shipped with a standard ArcGIS Pro installation.

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1.1 Import the package#

The following statement imports the arcgis library and several submodules that we use for to plotting maps in a Python Notebook.

import arcgis
from arcgis import GIS, GeoAccessor, GeoSeriesAccessor, pd

1.2 The GIS class from the gis module#

What is class in Python?

  • It is a blueprint for building things (a machine produces products)

  • Things get created from the class are called objects (or instances of the class)

  • DRY (Don’t repeat yourself) code.

  • Example classes: a college student or a car, or a data structure that organizes the data just as np.ndarray and pd.DataFrame.

What is GIS (Geographic Information System)?

  • Geographic Data:

    • collection

    • storage

    • manipulation

    • analysis

    • visualization

    • management/administration

    • distribution

  • A variety of technologies:

    • human activities (such as conducting survey of an area of land)

    • hardware

    • software (a narrower definition of GIS)

The arcgis.GIS:

  • a portal to do GIS in Python Notebooks

  • can link to an ArcGIS Online account

  • or, be used locally without the connection

2. Spatially Enabled DataFrame#

A Spatially Enabled DataFrame (SEDF) is a special type of pd.DataFrame that is part of the ArcGIS API for Python. It allows you to work with and analyze spatial data in Python, using the power of the Pandas library.

It is a class defined in the features module of arcgis (arcgis.features). It contains types and functions for working with features and feature layers in the GIS. Since it is an extension of pd.DataFrame class, meaning that it possesses all functions of a normal DataFrame.

We use ArcPy as the geometry engine for this module, which gives us access to all native GIS data ArcGIS Pro supports.

Now, let’s see how we can load a feature class as a “SEDF.”

from arcgis import pd, GeoAccessor, GeoSeriesAccessor
import arcpy

gdb_worksp = r"..\data\class_data.gdb"
arcpy.env.workspace = gdb_worksp
blkgrp_fc = "blockgroups"

blkgrp_sedf = pd.DataFrame.spatial.from_featureclass(blkgrp_fc)
blkgrp_sedf.head()
OBJECTID STATEFP10 COUNTYFP10 TRACTCE10 BLKGRPCE10 GEOID10 NAMELSAD10 MTFCC10 FUNCSTAT10 ALAND10 ... DEN_NOTWEL DEN_NOTATA PCT_OWN5 PCT_RENT5 PCT_BACHLR PCT_POV PCT_RU1 DATAYEAR DESCRIPT SHAPE
0 1 12 023 110903 2 120231109032 Block Group 2 G5030 S 57546992.0 ... 0.004918 0.000000 17.225951 62.878788 9.922481 23.488372 23.488372 REDISTRICTING, SF1, ACS 2010 120231109032 {"rings": [[[530441.2199999988, 651631.75], [5...
1 2 12 023 110904 1 120231109041 Block Group 1 G5030 S 85591551.0 ... 0.000329 0.000329 26.212320 58.015267 5.456656 4.102167 4.102167 REDISTRICTING, SF1, ACS 2010 120231109041 {"rings": [[[534712.1700000018, 663369.54], [5...
2 3 12 007 000300 5 120070003005 Block Group 5 G5030 S 196424609.0 ... 0.000021 0.000000 13.270142 68.181818 1.254613 10.701107 10.701107 REDISTRICTING, SF1, ACS 2010 120070003005 {"rings": [[[567924.9299999997, 665800.79], [5...
3 4 12 007 000300 4 120070003004 Block Group 4 G5030 S 16339411.0 ... 0.000000 0.000000 18.924731 73.711340 12.617839 14.902103 14.902103 REDISTRICTING, SF1, ACS 2010 120070003004 {"rings": [[[588576.3599999994, 644359.46], [5...
4 5 12 007 000300 1 120070003001 Block Group 1 G5030 S 57089369.0 ... 0.000000 0.001138 22.957198 43.333333 1.134021 21.161826 21.161826 REDISTRICTING, SF1, ACS 2010 120070003001 {"rings": [[[576256.1799999997, 656541.8300000...

5 rows × 202 columns

len(blkgrp_sedf)

178

blkgrp_sedf.shape

(178, 202)

blkgrp_sedf['TOTALPOP'].values

array([2094, 2269, 1305, 1991, 2056, 1410, 1890, 2510, 1150, 1856, 1455,
       1905, 2703,  865, 1735, 2330,  979, 1169, 2186, 3172,  163, 2175,
       2139, 2162,  999, 2124, 2278, 1600,  323, 2558, 2452, 1814, 4757,
       3260,  710,  911, 1391,  866, 2755,  798, 1937, 1166, 1246, 2329,
        924, 1779,  885,  665,  803,  844, 1418,  770, 1430,  568, 1193,
       1440,  777, 1806,  821, 1627, 1347, 1058, 2112, 1391, 1502, 1232,
       3088, 1077, 1174, 1155, 1582, 1130,  625, 1165, 1090, 1210, 2285,
       2171, 1604, 1957,  620, 1091, 1196,  642, 3589, 1433, 2906, 1930,
       5398, 1414, 1033,  993, 1345, 1482,  787, 1157, 1962, 1658, 1570,
       1973, 3617, 1270, 2497, 1522, 1356, 2877, 1323, 1741,  682,  833,
       1364,  895, 2482,  962,  838, 2136, 1567, 1255, 2030, 1269, 1154,
       1488, 2180,  703, 1066, 1861, 1515, 2027, 1061, 1067, 1851, 1614,
       1363, 1779, 1685, 1784,  696,  866, 1638, 1684, 3282, 1462,  386,
       2040,  662, 3641, 1431,  718, 2888, 1846, 2559, 1619, 1538,  963,
       2463,  696, 1070, 3415, 2034, 2613, 1138,  823, 3886, 2662, 2625,
        823,  836,  978, 1091,  637,  921, 1342, 2680, 1211, 1788, 1723,
       1189,  789], dtype=int64)

3. Visualizing spatial data#

3.1 Create a map object#

Before we can create a map, we need to set up a GIS instance that is connected to your ArcGIS Online account.

my_gis = GIS()

my_gis
GIS @ https://www.arcgis.com

Then, we can prepare SEDFs Loading data into the GIS instance

import arcpy
gdb_worksp = r"..\data\class_data.gdb"
arcpy.env.workspace = gdb_worksp

blkgrp = "blockgroups"
schools = 'schools'

blkgrp_sedf = pd.DataFrame.spatial.from_featureclass(blkgrp)
schools_sedf = pd.DataFrame.spatial.from_featureclass(schools)

Use the map() function to create a map widget from the GIS instance to create a map.

The location parameter takes a list of coordinates. And zoomlevel dictates how “zoomed-in” the map will be displayed initially. It is a value ranged between 0 (world) to 23 (house). Check this link to learn more.

my_map_in_my_gis = my_gis.map(location=[29.7, -82.3],
                              zoomlevel=9)

my_map_in_my_gis
mapwidget

3.2 Load SEDFs into the MapWidget#

Call spatial.plot() and specify the map_widget parameter to add the layer to a specific map. Note that SEDF loaded later will overlap the SEDFs loaded earlier.

blkgrp_sedf.spatial.plot(map_widget=my_map_in_my_gis)

schools_sedf.spatial.plot(map_widget=my_map_in_my_gis,
                          col='NAME', 
                          renderer_type='u')

my_map_in_my_gis
mapwidget-layers

3.3 Modify the size of the widget window#

from ipywidgets import Layout

my_map_in_my_gis.layout = Layout(height="600px")
my_map_in_my_gis
mapwidget-height 
my_map_in_my_gis.layout = Layout(width="600px", height="600px")
my_map_in_my_gis
mapwidget-width-height

3.3 Change the Basemap#

  1. basemaps attribute of a map returns a list of available basemaps

my_map_in_my_gis.basemaps

['dark-gray-vector',
 'gray-vector',
 'hybrid',
 'oceans',
 'osm',
 'satellite',
 'streets-navigation-vector',
 'streets-night-vector',
 'streets-relief-vector',
 'streets-vector',
 'terrain',
 'topo-vector',
 'arcgis-imagery',
 'arcgis-imagery-standard',
 'arcgis-imagery-labels',
 'arcgis-light-gray',
 'arcgis-dark-gray',
 'arcgis-navigation',
 'arcgis-navigation-night',
 'arcgis-streets',
 'arcgis-streets-night',
 'arcgis-streets-relief',
 'arcgis-topographic',
 'arcgis-oceans',
 'osm-standard',
 'osm-standard-relief',
 'osm-streets',
 'osm-streets-relief',
 'osm-light-gray',
 'osm-dark-gray',
 'arcgis-terrain',
 'arcgis-community',
 'arcgis-charted-territory',
 'arcgis-colored-pencil',
 'arcgis-nova',
 'arcgis-modern-antique',
 'arcgis-midcentury',
 'arcgis-newspaper',
 'arcgis-hillshade-light',
 'arcgis-hillshade-dark',
 'arcgis-human-geography',
 'arcgis-human-geography-dark']

Pick a basemap from the above list and assign it to the basemap attribute to the map widget.

my_map_in_my_gis.basemap = 'dark-gray-vector'
my_map_in_my_gis
mapwidget-dark

3.4 Choropleth Map#

A choropleth map is a type of thematic map that uses color to represent a quantitative variable (e.g., population) for different geographic regions, such as countries, states, or counties.

In a choropleth map, each region is shaded or colored based on its corresponding value for the variable being mapped. Regions with higher values are typically shaded with darker or more intense colors, while regions with lower values are shaded with lighter or less intense colors.

ArcGIS Python API provides a series of color maps to plot features on maps.

from arcgis import mapping

mapping.display_colormaps()
../_images/6-2.Intro_to_ArcGIS_API_for_Python_39_0.png 
map2 = my_gis.map(location=[29.7, -82.3], zoomlevel=9)

blkgrp_sedf.spatial.plot(map_widget=map2,
                         colors="YlGnBu",
                         col='TOTALPOP',
                         renderer_type='c',
                         method='esriClassifyNaturalBreaks',
                         class_count=7)
map2.layout = Layout(height="700px")
map2.basemap = "dark-gray-vector"
map2
mapwidget-choropleth